diff --git a/docs/source/custom_datasets.rst b/docs/source/custom_datasets.rst
index d28373c55..06a85010d 100644
--- a/docs/source/custom_datasets.rst
+++ b/docs/source/custom_datasets.rst
@@ -558,15 +558,13 @@ we can use the built in :func:`~transformers.BatchEncoding.char_to_token` method
         end_positions = []
         for i in range(len(answers)):
             start_positions.append(encodings.char_to_token(i, answers[i]['answer_start']))
-            end_positions.append(encodings.char_to_token(i, answers[i]['answer_end']))
+            end_positions.append(encodings.char_to_token(i, answers[i]['answer_end'] - 1))
 
             # if start position is None, the answer passage has been truncated
             if start_positions[-1] is None:
                 start_positions[-1] = tokenizer.model_max_length
+                end_positions[-1] = tokenizer.model_max_length
 
-            # if end position is None, the 'char_to_token' function points to the space before the correct token - > add + 1
-            if end_positions[-1] is None:
-                end_positions[-1] = encodings.char_to_token(i, answers[i]['answer_end'] + 1)
         encodings.update({'start_positions': start_positions, 'end_positions': end_positions})
 
     add_token_positions(train_encodings, train_answers)